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UPLC-Q-TOF-MS profiling of the hippocampus reveals metabolite biomarkers for the impact of Dl-3-n-butylphthalide on the lipopolysaccharide-induced rat model of depression

Authors Geng C, Guo Y, Qiao Y, Zhang J, Chen D, Han W, Yang M, Jiang P

Received 1 February 2019

Accepted for publication 10 June 2019

Published 10 July 2019 Volume 2019:15 Pages 1939—1950

DOI https://doi.org/10.2147/NDT.S203870

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Prof. Dr. Roumen Kirov

Peer reviewer comments 3

Editor who approved publication: Dr Yu-Ping Ning


Chunmei Geng,*,1 Yujin Guo,*,1 Yi Qiao,2 Jun Zhang,3 Dan Chen,1 Wenxiu Han,1 Mengqi Yang,1 Pei Jiang1

1Institute of Clinical Pharmacy and Pharmacology, Jining First People’s Hospital, Jining Medical University, Jining, People’s Republic of China; 2Department of Public Health, Jining Medical University, Jining, People’s Republic of China; 3Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China

*These authors contributed equally to this work

Purpose: An increasing body of evidence reveals that inflammation is involved in the pathological mechanisms of depression. Our previous basic research confirmed that Dl-3-n-butylphthalide (NBP) possess anti-inflammatory properties. However, studies investigating metabolite biomarkers for the involvement of NBP in hippocampus tissue in the lipopolysaccharide (LPS)-induced rat model of depression are currently limited. Thus, the aim of this study was to identify metabolite biomarkers in the hippocampus for the impact of NBP in this model of depression.
Material and methods: Male Sprague–Dawley rats were randomly allocated to one of the following three groups (n=6): Control, LPS-induced rat model of depression (LPS), and NBP involvement in the LPS-induced rat model of depression (LPS+NBP). Ultra-high-performance liquid chromatography-mass spectroscopy was used to determine the hippocampal metabolites. Multivariate statistical analysis was performed to identify differentially expressed hippocampal metabolites in the three groups.
Results: Most of the identified differentially expressed metabolites were related to amino acid, lipid, energy, and oxidative stress metabolism. Additionally, metabolites were eventually connected to different pathways and metabolic networks, which may partly account for the pathophysiological process of depression.
Conclusion: The present findings provide insight into the anti-inflammatory effects of NBP, and further elucidate the pathophysiological mechanisms underlying inflammation-induced depression.

Keywords: inflammation, Dl-3-n-butylphthalide, lipopolysaccharide, metabolite biomarkers, ultra-high-performance liquid chromatography-mass spectroscopy


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